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Paper Citation Record · LEDGER

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving

As of 20 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2505.15793.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.15793 v2

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:13:45.072007Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

60 of 60 outbound references displayed

  • verified exact5
  • verified fuzzy18
  • unresolved37
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ff2bf7b7-d52d-45aa-9f95-9e1c3d040280 · outbound

This paper cites Reinforcement learning algorithms: A brief survey.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Reinforcement learning algorithms: A brief survey

Reference 1

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ee4e5cd9-eb1f-478a-a4fa-e22e84b9b71e · outbound

This paper cites Deep reinforcement learning: A survey.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Deep reinforcement learning: A survey

Reference 2

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source=pdf_text observed=2026-08-07T15:13:38.089874Z digest=sha256:c555d8df1deb4f1d698ca9f2c29d77862ccdf0c62eebaf3486e51af1c017a6bd

Observation dd28ad47-5f5d-446c-9af6-b2b9d975e6f5 · outbound

This paper cites A Review of Safe Reinforcement Learning: Methods, Theory and Applications.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 3

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source=pdf_text observed=2026-08-07T15:13:38.190951Z digest=sha256:ab66023d8053cf33c886d26a4578c43708aef77bade755b248cfe70c5c51fa90

Observation d2fb4b9c-c9e0-4703-89e4-3e604ed0c6d0 · outbound

This paper cites Milestones in autonomous driving and intelligent vehicles: Survey of surveys.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Milestones in autonomous driving and intelligent vehicles: Survey of surveys

Reference 4

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raw_fallback, observed 2026-08-07T15:13:50.991617Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:38.291323Z digest=sha256:6d7778369aedc4ff916840981ba546279515d88c36f22423327fe9147f5fe270

Observation 09ea864e-390f-4e7d-a28e-99d38fa1a72d · outbound

This paper cites Event-triggered model predictive control with deep reinforcement learning for autonomous driving.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Event-triggered model predictive control with deep reinforcement learning for autonomous driving

Reference 5

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:38.501592Z digest=sha256:f6f5a0ed953c46ab01e5b7cad0a2ac2adc3ded885ba3cfbd6ec165844b3bbc93

Observation 4d6fcc8d-e843-4e4e-af27-db0d689266da · outbound

This paper cites Deep reinforcement learning with nmpc assistance nash switching for urban autonomous driving.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Deep reinforcement learning with nmpc assistance nash switching for urban autonomous driving

Reference 6

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source=pdf_text observed=2026-08-07T15:13:38.617508Z digest=sha256:7f248ade8cd73090000256a84a91c2eb2dec892adc9cf4188de18a2ca3892038

Observation f3defba4-44d7-4ada-9197-f848bd7dcbc0 · outbound

This paper cites Language models are few-shot learners.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Language models are few-shot learners

Reference 7

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source=pdf_text observed=2026-08-07T15:13:38.717304Z digest=sha256:f565fc409eda6266fbec1fa8c548663bf48fe1b296ef9ad69644918f5f5b9688

Observation 0275447b-62ec-49de-8395-410dab057a5e · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving LLaMA: Open and Efficient Foundation Language Models

Reference 8

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source=pdf_text observed=2026-08-07T15:13:38.938324Z digest=sha256:918d0f80f3582a03d4a879f3a434ab13f2d674cbaa24aee4dc4eac669f5e03df

Observation b8f3bdbb-7e1e-4f7f-a01c-f7b19cb183a8 · outbound

This paper cites Explain Yourself! Leveraging Language Models for Commonsense Reasoning.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Explain Yourself! Leveraging Language Models for Commonsense Reasoning

Reference 9

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source=pdf_text observed=2026-08-07T15:13:39.086618Z digest=sha256:f4ed8f87c1dea556a2538dfd35fac515fe62f167a150edf055caddb63ac3f018

Observation f7eb0243-a63e-4bfe-9e2b-a2af77a3eb0a · outbound

This paper cites Can Large Language Models Explain Themselves? A Study of LLM-Generated Self-Explanations.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Can Large Language Models Explain Themselves? A Study of LLM-Generated Self-Explanations

Reference 10

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source=pdf_text observed=2026-08-07T15:13:39.160195Z digest=sha256:3c15375a06b83b17dc2b0e5f10e3245002e4ecb030f752be125e006f50978045

Observation bce1d8a1-66bd-4254-8282-05cb920efc09 · outbound

This paper cites The Llama 3 Herd of Models.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving The Llama 3 Herd of Models

Reference 11

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source=pdf_text observed=2026-08-07T15:13:39.232635Z digest=sha256:9cd4b34705d36df384b0887cf3fa65ff31768c23e79eb31f82ae4dd983eab02b

Observation 4ee9c737-24d7-4521-a350-52090cc44a5a · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 12

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source=pdf_text observed=2026-08-07T15:13:39.381567Z digest=sha256:7c6826335732044e1afb8e7280fc7af93f12ccd972da6a1a28dbf87847e6fdcc

Observation 78af3939-c290-4f45-b8ad-fafe89bd5cda · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 13

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source=pdf_text observed=2026-08-07T15:13:39.513175Z digest=sha256:5422d06fd3c2c322e9567cbcd5bb70e8365cfdf89ee2f12a2c24f759c65461ab

Observation 55b60325-e9b7-4c16-a5ea-122aa48d87cf · outbound

This paper cites Limsim++: A closed-loop platform for deploying multimodal llms in autonomous driving.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Limsim++: A closed-loop platform for deploying multimodal llms in autonomous driving

Reference 14

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raw_fallback, observed 2026-08-07T15:13:50.317088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:39.649174Z digest=sha256:26a0e8003960a8916a6037d4e46fd21e98b7508f9f966da60d1f5a7380f55338

Observation 88f47f00-536c-4284-ba38-83acc0b6a09d · outbound

This paper cites Lampilot: An open benchmark dataset for autonomous driving with language model programs.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Lampilot: An open benchmark dataset for autonomous driving with language model programs

Reference 15

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:39.724284Z digest=sha256:ce66747c4575f14e6c29fc95f91ae12027df6be804aaf5e9e58b0feb3ffdbeac

Observation 2b00062c-5c10-4411-b073-9d8a3d1485ca · outbound

This paper cites DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Driving.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Driving

Reference 16

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source=pdf_text observed=2026-08-07T15:13:39.870729Z digest=sha256:914b0d30b68270a0263007b2c119835f5ab507738bd7756633d4be871a32f522

Observation a137705b-f166-4471-b83e-099d205cdab0 · outbound

This paper cites Driving with llms: Fusing object-level vector modality for explainable autonomous driving.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Driving with llms: Fusing object-level vector modality for explainable autonomous driving

Reference 17

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source=pdf_text observed=2026-08-07T15:13:40.028157Z digest=sha256:e37b48f262061308a21df981563e7f916ba50e5b0a3964031904bf403c02a658

Observation dedc060e-f68f-46ea-a839-b7e2bbb88b15 · outbound

This paper cites LLM4Drive: A Survey of Large Language Models for Autonomous Driving.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving LLM4Drive: A Survey of Large Language Models for Autonomous Driving

Reference 18

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source=pdf_text observed=2026-08-07T15:13:40.153066Z digest=sha256:328f81f40ee4b3bdc9ea434e5bea528b57b232e93430fff95d49e336bd78c670

Observation 28a9d241-289f-4a2c-987c-3e51f00bef1a · outbound

This paper cites Survey on large language model-enhanced reinforcement learning: Concept, taxonomy, and methods.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Survey on large language model-enhanced reinforcement learning: Concept, taxonomy, and methods

Reference 19

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source=pdf_text observed=2026-08-07T15:13:40.272522Z digest=sha256:4bf9452e779da4a8d325bebaf6e61baecaebf253d6b4aa33c31e51fe9b8f6d40

Observation bbb02410-a701-4f50-8c2a-5f685df8c4e4 · outbound

This paper cites The Evolving Landscape of LLM- and VLM-Integrated Reinforcement Learning.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving The Evolving Landscape of LLM- and VLM-Integrated Reinforcement Learning

Reference 20

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local_arxiv, observed 2026-08-07T15:13:46.682510Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:40.383369Z digest=sha256:70b3820c7c1db64b2eae8a8308a9311dbd853f1ae41a854678c7c0500d84680c

Observation 8bb67715-276b-401c-8a10-4e6772e4e2ac · outbound

This paper cites Robust RL with LLM-Driven Data Synthesis and Policy Adaptation for Autonomous Driving.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Robust RL with LLM-Driven Data Synthesis and Policy Adaptation for Autonomous Driving

Reference 21

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local_arxiv, observed 2026-08-07T15:13:46.325224Z

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source=pdf_text observed=2026-08-07T15:13:40.499557Z digest=sha256:e4e7c69d533a11e9db90048571e875968271de750bd423e6fc7bc349f19a49d0

Observation 3b0f2862-310e-474d-b8e6-c4f75ddf3572 · outbound

This paper cites HighwayLLM: Decision-Making and Navigation in Highway Driving with RL-Informed Language Model.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving HighwayLLM: Decision-Making and Navigation in Highway Driving with RL-Informed Language Model

Reference 22

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local_arxiv, observed 2026-08-07T15:13:46.115841Z

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source=pdf_text observed=2026-08-07T15:13:40.692441Z digest=sha256:6f54ec58be5cc7ee25ca1f12c19f11d77e427edb3431a75ccb7592dbef524d81

Observation 719611fb-4ff4-4c10-a221-4350bbb118fb · outbound

This paper cites AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning

Reference 23

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source=pdf_text observed=2026-08-07T15:13:40.813952Z digest=sha256:07d208724a87179cebdbab0cd4d6e11e5b047ad2a815eb4591bdb75526a0b95b

Observation d8c34570-3f2e-4e6e-b1f3-48ecccf7f080 · outbound

This paper cites Optimizing autonomous driving for safety: A human- centric approach with llm-enhanced rlhf.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Optimizing autonomous driving for safety: A human- centric approach with llm-enhanced rlhf

Reference 24

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source=pdf_text observed=2026-08-07T15:13:40.932576Z digest=sha256:b641bc3681aaec1a5ee75d93348edd6aad2045ad1c8a125b563cb083344b9e94

Observation 028119a4-8591-4506-b4d8-fd400be7334f · outbound

This paper cites VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Driving.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Driving

Reference 25

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source=pdf_text observed=2026-08-07T15:13:41.080485Z digest=sha256:389df1d12a9fc8534099c353932d2f094d542e3ecdae53c745bee7efa37c6bb6

Observation 4f77f1af-e24f-4541-94ba-e7b2d231e8be · outbound

This paper cites CurricuVLM: Towards Safe Autonomous Driving via Personalized Safety-Critical Curriculum Learning with Vision-Language Models.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving CurricuVLM: Towards Safe Autonomous Driving via Personalized Safety-Critical Curriculum Learning with Vision-Language Models

Reference 26

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source=pdf_text observed=2026-08-07T15:13:41.227622Z digest=sha256:4949c0f5a179bcfa5eeefe51f0108223dddad3da6ecd9515d7ae7327c0be1bf7

Observation 65197cca-5cf8-4ba5-975b-8edfac03eb4c · outbound

This paper cites Large Language Model guided Deep Reinforcement Learning for Decision Making in Autonomous Driving.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Large Language Model guided Deep Reinforcement Learning for Decision Making in Autonomous Driving

Reference 27

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source=pdf_text observed=2026-08-07T15:13:41.382693Z digest=sha256:050186954ef61a8bc7d82f66feaeb8e1a3bd72e759f033065bc4584aa361549e

Observation eedf6962-2325-4712-84a7-9fae99fe9538 · outbound

This paper cites LearningFlow: Automated Policy Learning Workflow for Urban Driving with Large Language Models.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving LearningFlow: Automated Policy Learning Workflow for Urban Driving with Large Language Models

Reference 28

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local_arxiv, observed 2026-08-07T15:13:45.844889Z

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source=pdf_text observed=2026-08-07T15:13:41.473724Z digest=sha256:4c55605aa838cbbc578848f453c792228c40e9fd1dd99fbbadeac86a4a8ea9ae

Observation c08755b0-b041-4819-8163-c018abebf8ee · outbound

This paper cites Autoreward: Closed-loop reward design with large language models for autonomous driving.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Autoreward: Closed-loop reward design with large language models for autonomous driving

Reference 29

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:41.537346Z digest=sha256:633c78254957937b0c76f6e05315b3bfadce7071b9e223eb1a07fdc3dd73446c

Observation c6dafbe8-d84c-488d-a6ec-cc2581ec03af · outbound

This paper cites CLIP-RLDrive: Human-Aligned Autonomous Driving via CLIP-Based Reward Shaping in Reinforcement Learning.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving CLIP-RLDrive: Human-Aligned Autonomous Driving via CLIP-Based Reward Shaping in Reinforcement Learning

Reference 30

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source=pdf_text observed=2026-08-07T15:13:41.718661Z digest=sha256:83432eac7a2e562aebf22cccd85a5936c0d6ee5158b9cb160c205e9dfda561d3

Observation de4a2223-a3f9-40ad-a2c7-57e517325fb0 · outbound

This paper cites Lord: Large models based opposite reward design for autonomous driving.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Lord: Large models based opposite reward design for autonomous driving

Reference 31

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raw_fallback, observed 2026-08-07T15:13:49.575694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:41.859641Z digest=sha256:a33347b7fe92fef0dc355a68beb9926474bce54fb6d560bd28e1864f988d6cbe

Observation 25070fe4-6866-4766-89c1-5049edc80bd4 · outbound

This paper cites Revolve: Reward evolution with large language models for autonomous driving.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Revolve: Reward evolution with large language models for autonomous driving

Reference 32

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raw_fallback, observed 2026-08-07T15:13:49.439504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:42.042418Z digest=sha256:bcb0f1b9ef1b7b8592c48e5a5a7c48b860f082781791c5af7cefaba308120065

Observation 4c469ab0-84ef-4ea2-a378-04983c3998fa · outbound

This paper cites LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations

Reference 33

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source=pdf_text observed=2026-08-07T15:13:42.187476Z digest=sha256:b5b2a8aa25cbaab3b9c1c84819f63a90f120b7b61a651239d07013091dd54b96

Observation 51089c0c-b0b6-4b7e-88ff-5d6cb44f2434 · outbound

This paper cites CrossCheckGPT: Universal Hallucination Ranking for Multimodal Foundation Models.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving CrossCheckGPT: Universal Hallucination Ranking for Multimodal Foundation Models

Reference 34

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local_arxiv, observed 2026-08-07T15:13:45.640239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:42.283847Z digest=sha256:38fd09bb1f03474b366033bcada9456a5ce3598cd7ce59bee00c10e8371b7af7

Observation 04727cb5-68c5-4358-9e31-298b38c9dac5 · outbound

This paper cites LLM Hallucinations in Practical Code Generation: Phenomena, Mechanism, and Mitigation.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving LLM Hallucinations in Practical Code Generation: Phenomena, Mechanism, and Mitigation

Reference 35

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source=pdf_text observed=2026-08-07T15:13:42.420652Z digest=sha256:9d5661fb247d0e0785f1dc446f76ea77dfa24883910f1c538010cca67f1c09b2

Observation 08e6e69b-2aeb-438e-baf7-85869b80993c · outbound

This paper cites Exploring and evaluating hallucinations in llm-powered code generation.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Exploring and evaluating hallucinations in llm-powered code generation

Reference 36

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source=pdf_text observed=2026-08-07T15:13:42.543190Z digest=sha256:ec7cd16a41f356b4ef279346752549e4961aef855a50701085697b7f0d4425ce

Observation 61c8658f-51b8-47dc-871c-ec81121c270f · outbound

This paper cites Llm-check: Investigating detection of hallucinations in large language models.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Llm-check: Investigating detection of hallucinations in large language models

Reference 37

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verified fuzzy
raw_fallback, observed 2026-08-07T15:13:49.318571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:42.589997Z digest=sha256:01fb0c8d3ec2b94370aae002cc81edadbaf095a9628da380b2ddb62f8ce8e61d

Observation 2347f6aa-ac5a-4b8b-a3da-97312c56f293 · outbound

This paper cites STI-Bench: Are MLLMs Ready for Precise Spatial-Temporal World Understanding?.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving STI-Bench: Are MLLMs Ready for Precise Spatial-Temporal World Understanding?

Reference 38

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source=pdf_text observed=2026-08-07T15:13:42.676327Z digest=sha256:f47b62487baaa02b689ab22599bc6876c1b6348934da1a8282cb6fed3b268478

Observation d8f7bdbf-a887-488d-a79a-3bbfa68c98ea · outbound

This paper cites Rladapter: Bridging large language models to reinforcement learning in open worlds.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Rladapter: Bridging large language models to reinforcement learning in open worlds

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-07T15:13:49.135974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:42.860628Z digest=sha256:ff532ed37b7afbff5093854249ea32d0c1f2ac51ce45be2d6c0fd313e9b71acf

Observation 386ce246-dca3-4fd5-a1a8-e2456d0e1088 · outbound

This paper cites Pre-trained language models for interactive decision-making.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Pre-trained language models for interactive decision-making

Reference 40

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source=pdf_text observed=2026-08-07T15:13:42.954660Z digest=sha256:27e3cd66833c89d686dced85cc425f46401fd8ebfb86907e9d80ef1845ee275d

Observation 6f3765b7-752a-414c-acc6-0bb795585cde · outbound

This paper cites Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning

Reference 41

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source=pdf_text observed=2026-08-07T15:13:43.083091Z digest=sha256:df8c01bcc343439febfe61852a53978ba89645e85bf688e3e15ad1b1ff4a3918

Observation 0b0e9a00-1d26-47d0-8065-0e726e961abf · outbound

This paper cites Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models

Reference 42

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source=pdf_text observed=2026-08-07T15:13:43.182597Z digest=sha256:79d451f623b728e10745a73bf952d3aa4e859a1f8c3e601931eb435ae1747049

Observation 305b7bed-a869-4f01-8ebc-60d8f37803b9 · outbound

This paper cites Efficient Reinforcement Learning with Large Language Model Priors.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Efficient Reinforcement Learning with Large Language Model Priors

Reference 43

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source=pdf_text observed=2026-08-07T15:13:43.329899Z digest=sha256:0e3a663de437e07f08a5fc955afd6a791333494ef4ee5b5f865871574172df02

Observation a44a4276-8fdd-4bfc-b637-45f8fa8ca24e · outbound

This paper cites Grounding large language models in interactive environments with online reinforcement learning.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Grounding large language models in interactive environments with online reinforcement learning

Reference 44

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verified fuzzy
raw_fallback, observed 2026-08-07T15:13:48.956077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:43.429434Z digest=sha256:337d833a38113eec7877d3bb6068b7e977161bda197b593246b047265097d30a

Observation f8be9a38-554c-4843-ad3b-a756f3556c6b · outbound

This paper cites Fine-tuning large vision-language models as decision-making agents via reinforcement learning.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Fine-tuning large vision-language models as decision-making agents via reinforcement learning

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-07T15:13:48.691903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:43.509924Z digest=sha256:1196b426159dfa58d25c84781a0726309c1be4ef29a32576b9ead53ec1bf8c22

Observation 49fc1608-b320-4489-bbfa-ae4d409b03ac · outbound

This paper cites Teaching Large Language Models to Reason with Reinforcement Learning.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Teaching Large Language Models to Reason with Reinforcement Learning

Reference 46

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source=pdf_text observed=2026-08-07T15:13:43.610133Z digest=sha256:ad562280d4eb05d82d3588e14af4c06c810c5921adc6784d480af46b8fef7dd1

Observation 39dd5d8d-80d1-4511-941a-70db42fcaf31 · outbound

This paper cites Latent reward: Llm-empowered credit assignment in episodic reinforcement learning.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Latent reward: Llm-empowered credit assignment in episodic reinforcement learning

Reference 47

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raw_fallback, observed 2026-08-07T15:13:48.459332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:43.722332Z digest=sha256:cff982ec8686ebff012aa626bcf25d26a3b07f8566e4189838de69b4736c0ccc

Observation 869f221a-4444-4f51-bd69-bb2e6a21cab0 · outbound

This paper cites Text2Reward: Reward Shaping with Language Models for Reinforcement Learning.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Text2Reward: Reward Shaping with Language Models for Reinforcement Learning

Reference 48

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source=pdf_text observed=2026-08-07T15:13:43.841984Z digest=sha256:0feafd9b7f206616b56895cf3500d92cd7a4c2b5fefe9b78213be397c9fcccdf

Observation e940e4c9-cec3-478d-ae1a-6dbb6b0c12ed · outbound

This paper cites LMPriors: Pre-Trained Language Models as Task-Specific Priors.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving LMPriors: Pre-Trained Language Models as Task-Specific Priors

Reference 49

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source=pdf_text observed=2026-08-07T15:13:43.958248Z digest=sha256:a6b8e70d97c619442bf8d059947e274d17087c98fcf33858ff42c225fb42f33f

Observation c358db97-b953-4c50-a735-7a8a38bdc92e · outbound

This paper cites Guiding pretraining in reinforcement learning with large language models.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Guiding pretraining in reinforcement learning with large language models

Reference 50

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verified fuzzy
raw_fallback, observed 2026-08-07T15:13:48.198912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:44.043046Z digest=sha256:e3aec3abb8d9876a88aa09445c4e42817d42fe3ad9052fc2c6b6b612abacb3a3

Observation 8ac7e83e-5021-4a5d-8aa8-a77f1b2d40bf · outbound

This paper cites Eureka: Human-Level Reward Design via Coding Large Language Models.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Eureka: Human-Level Reward Design via Coding Large Language Models

Reference 51

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source=pdf_text observed=2026-08-07T15:13:44.120140Z digest=sha256:c862d1d66bda7560fa40d3380028dd015e8544d2848de010c99ae553178ae3b9

Observation 649aa1a4-53e4-4146-b8c7-1144ed8be791 · outbound

This paper cites Shufflenet v2: Practical guidelines for efficient cnn architecture design.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Shufflenet v2: Practical guidelines for efficient cnn architecture design

Reference 52

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source=pdf_text observed=2026-08-07T15:13:44.247133Z digest=sha256:46206bcf3d292e28dd9df8a957ba02b095d1e1fb83e29ab702277b0b7281613f

Observation 4999fcf0-a1ce-451e-a25a-a8d5fd7f9ba5 · outbound

This paper cites Proximal Policy Optimization Algorithms.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Proximal Policy Optimization Algorithms

Reference 53

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source=pdf_text observed=2026-08-07T15:13:44.372579Z digest=sha256:91ec10770062b4a410531f6548b6507951d524221d21208f6ecea822dc083d5b

Observation df58aec2-3e55-45fb-8d7e-0f58277e824d · outbound

This paper cites Retrieval-augmented generation for knowledge- intensive nlp tasks.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Retrieval-augmented generation for knowledge- intensive nlp tasks

Reference 54

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source=pdf_text observed=2026-08-07T15:13:44.417563Z digest=sha256:5e62aaec29abac88a6ba86f2bf172554ba9a169a21333bef61ae4f764c6e95cd

Observation df81cc2c-9184-42ad-8da9-b16693c0deb5 · outbound

This paper cites Driving with regulation: Interpretable decision-making for autonomous vehicles with retrieval-augmented reasoning via llm.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Driving with regulation: Interpretable decision-making for autonomous vehicles with retrieval-augmented reasoning via llm

Reference 55

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source=pdf_text observed=2026-08-07T15:13:44.473392Z digest=sha256:9b90014d78155a74307d74060975344cafa64ff38e7270b2d9e4d4b5de79dc11

Observation 8107abfc-1589-46f6-a2e0-3326276dc0bf · outbound

This paper cites Rag-driver: Generalisable driving explanations with retrieval-augmented in-context learning in multi-modal large language model.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Rag-driver: Generalisable driving explanations with retrieval-augmented in-context learning in multi-modal large language model

Reference 56

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T15:13:44.607686Z digest=sha256:a88bf02d06dff5e7f6c31dcd9c87ad78378da96f21a77e1458a0bf12ff14e79a

Observation aca40825-2ce7-436a-b106-689c7f1c11e9 · outbound

This paper cites Billion-scale similarity search with gpus.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Billion-scale similarity search with gpus

Reference 57

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source=pdf_text observed=2026-08-07T15:13:44.726077Z digest=sha256:3e595fc97b07fdcfdf7d3b2117590234f95ebd02417ec49fcc38f2e1bda490f3

Observation 91c11edf-32d0-4aae-bb79-d51caa1c1e9a · outbound

This paper cites Carla: An open urban driving simulator.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Carla: An open urban driving simulator

Reference 58

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T15:13:44.834069Z digest=sha256:23b5a1858c916eb2db2ccb3a09cfaab60443878ac7446e906e0f557f9c17bde5

Observation 5b5fd332-5878-418a-bd71-ba438cc30a95 · outbound

This paper cites An end-to-end curriculum learning approach for autonomous driving scenarios.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving An end-to-end curriculum learning approach for autonomous driving scenarios

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:13:47.587803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:44.950989Z digest=sha256:d918bdd41824a7793c145b5f3716072e84867c60619d297c25432b68a44a0002

Observation 1b51b106-22e6-48b1-b840-d293a1d5ee2a · outbound

This paper cites Standards for passenger comfort in automated vehicles: Acceleration and jerk.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Standards for passenger comfort in automated vehicles: Acceleration and jerk

Reference 60

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verified fuzzy
raw_fallback, observed 2026-08-07T15:13:47.450614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:13:45.072007Z digest=sha256:5cd056af10285a396b3b53426fef59b0eeb06af342d51209c46249480021a9fa

Pith citing papers

No inbound Pith citation observations are available.